Measuring Labor Market Slack: Are the Long-Term Unemployed Different?
In today’s post, we consider several important characteristics of long-term unemployed workers and compare them to the characteristics of three other groups of potential workers: the short-term unemployed, nonparticipants who report that they want a job, and nonparticipants who do not want a job (whom we refer to as “other nonparticipants”). We distinguish between the two types of nonparticipants because previous literature established that the former group has stronger ties to the labor market (see Hornstein, Kudlyak, Lange, and Sablik , Jones and Riddell , and Krusell, Mukoyama, Rogerson, and Sahin [2010, 2011]). The charts below present the four groups with the color coding that we use throughout the blog series. Data are computed from the Current Population Survey (CPS) micro data; the CPS, produced by the Census Bureau and the Bureau of Labor Statistics, is the U.S. government's monthly survey of unemployment and labor force participation.
As shown in the chart on the upper left, the short-term and long-term unemployed have a similar gender composition, with a little more than half being males in each group. In contrast, for both types of nonparticipants, females are more common. In terms of age, the short-term unemployed and the nonparticipants who want a job have a greater concentration of those age 16 to 24 than the long-term unemployed. Otherwise, all three groups are broadly similar, with the prime-age workers (25 to 54) representing the largest share. Other nonparticipants are distributed much differently, with the vast majority age 55 and above. Meanwhile, racial composition of all four groups is very similar, with a slightly larger share of African Americans among the long-term unemployed. And the split by education is nearly identical in all four groups; high school dropouts are only slightly more common among both groups of nonparticipants.
Finally, we consider the occupation and industry composition of short- and long-term unemployed workers, classified by their former jobs. As the following two charts show, they are remarkably similar.
On the basis of these observable characteristics, we find that long-term unemployed workers are not less attached to the labor market than short-term unemployed workers. If anything, the long-term unemployed group has the largest share of prime-age workers, the age group likely to have the strongest labor force attachment. We also see that long-term unemployment is an economy-wide phenomenon, spread across industries and occupations. While there may be unobservable characteristics of long-term unemployed workers that make them less attached to the labor force, when looking at their observable characteristics, it’s hard to argue that they should not be considered as part of labor market slack.
In our next blog post, we study the labor market outcomes of long-term unemployed workers in an effort to assess their employability and labor market attachment. While the long-term unemployed have a lower chance of finding jobs than the short-term unemployed, they do so at a rate considerably higher than nonparticipants. In addition, conditional on finding jobs, the short- and long-term unemployed are about equally likely to find full-time jobs. The long-term unemployed also show much stronger attachment to the labor force than nonparticipants.
In our final blog post, we directly test the relationship between different unemployment-based measures of slack and the monthly earnings of new hires. Our analysis suggests that there is little difference in how long- and short-term unemployment affect wages, and as a consequence, the long-term unemployed should not be ignored when estimating labor market slack.
The views expressed in this post are those of the authors and do not necessarily reflect the position of the Federal Reserve Bank of New York or the Federal Reserve System. Any errors or omissions are the responsibility of the authors.
Robert C. Dent is a research analyst in the Federal Reserve Bank of New York’s Research and Statistics Group.
Samuel Kapon is a senior research analyst in the Bank’s Research and Statistics Group.
Fatih Karahan is an economist in the Bank’s Research and Statistics Group.
Benjamin Pugsley is an economist in the Bank’s Research and Statistics Group.
Ayşegül Sahin is an assistant vice president in the Bank’s Research and Statistics Group.